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Pengyi Shi is an Associate Professor at Purdue University's Krannert School of Management, having joined in January 2014. He has a Ph.D. in Industrial and Systems Engineering from the Georgia Institute of Technology. His research is centered around devising data-driven, high-fidelity models that develop predictive and prescriptive analytics to support decision-making within healthcare service systems. A significant focus of his work includes enhancing patient flow models to improve hospital operations and patient outcomes. Dr. Shi's methodologies encompass stochastic models, queueing theory, Markov decision processes, and various machine learning techniques, including reinforcement learning and online learning. He has actively contributed to tools that support inpatient discharge management, especially in light of the COVID-19 pandemic. Outside of healthcare, he has worked on predictive operations tools within the criminal justice system. His work aims not only to address immediate operational challenges but also to foresee and alleviate systemic stresses in these critical sectors.
Purdue University • West Lafayette, IN
Joined Purdue's Krannert School of Management, focusing on Operations Management.
GRE is not required.